Screening paper formation variations on production line

Authors:
Marcus Ejnarsson;Carl Magnus Nilsson;Antanas Verikas
Affiliations:
Intelligent Systems Laboratory, Halmstad University, Halmstad, Sweden;Intelligent Systems Laboratory, Halmstad University, Halmstad, Sweden;Intelligent Systems Laboratory, Halmstad University, Halmstad, Sweden and Department of Applied Electronics, Kaunas University of Technology, Kaunas, Lithuania
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

Citing 3
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Informatica
A kernel based multi-resolution time series analysis for screening deficiencies in paper production

ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III

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Abstract

This paper is concerned with a multi-resolution tool for screening paper formation variations in various frequency regions on production line. A paper web is illuminated by two red diode lasers and the reflected light recorded as two time series of high resolution measurements constitute the input signal to the papermaking process monitoring system. The time series are divided into blocks and each block is analyzed separately. The task is treated as kernel based novelty detection applied to a multi-resolution time series representation obtained from the band-pass filtering of the Fourier power spectrum of the series. The frequency content of each frequency region is characterized by a feature vector, which is transformed using the canonical correlation analysis and then categorized into the inlier or outlier class by the novelty detector. The ratio of outlying data points, significantly exceeding the predetermined value, indicates abnormalities in the paper formation. The tools developed are used for online paper formation monitoring in a paper mill.